Study Of Resistance Calculation And Form Parameter Optimization Of Planing Hull

With the development of ship hydrodynamics and artificial intelligence technology, theapplication of Unmanned Surface Vehicle (USV) has attracted great attentions recently. TheUSV shows great perspective in military and civil operations, for instance, mine deletion,water surface surveillance and target boat, consequently, many advanced countries are intendto carry out in-depth investigations on.Through a wide surveying, it can be clearly found that most of the USV are of PlaningHull Vehicle(PHV). Due to requirements of tough tasks, high speed and endurance ability areexpected as the most important factors for a USV. Hull shape optimization is essential for aUSV to reduce residence. As contrast to displacement hull vehicles, PHV is lifted partly byfluid hydrodynamic force, and the running attitudes totally depend on navigational speed,which makes it difficult to predict its resistance. In the present study, two methods areconducted to improve ship residence monitor ability, and suggestions about hull shape designsfor residence reduction are given based on several ships in different conditions.Numerical simulations are carried out by a Computational Fluid Dynamic (CFD)software Star-CCM+. A PHV model with6-DOF is simulated in calm water, keeping constantthe average dead rise of its bottom between mid-ship and stern, the change of resistance andship running attitude along the longitudinal direction are investigated analyzed. By a systemicanalysis of the simulation results, it is found that the position of fluid separation point andpressure distribution rely on dead rise angle near the stern when the averaged dead rise anglebeing kept as a constant, which can result in a change of ship running attitude and residence.It also shows that navigating propelling efficiency can be improved by increasing the deadrise angle and decreasing it near the stern properly. It is noticed that there is a criterion fordead rise angle near the stern, over which, PHV may tend to follow a bow down trim and thebottom pressure at the stern will be much bigger than that near the bow. Both of these mayinduce a high resistance, moreover, and harmful to the motion steadiness.In addition, a new concept based on the combination of a systematic model test data, BPNeutral Network method with optimised Genetic Algorithm is presented to improve theresistance prediction of PHV, and the relevant detailed factors and parameters are indicated inthis thesis. This new concept is effective in improving the resistance prediction accuracy,which has been validated by plenty results in this thesis.And finally, the method developed as presented above is used, combining with theGenetic Algorithm technique, to optimize the design parameter of a planing hull for drag reduction.